require(lolR)
## Loading required package: lolR
require(ggplot2)
## Loading required package: ggplot2
require(MASS)
## Loading required package: MASS
n=400
d=30
r=3
Data for this notebook will be n=400
examples of d=30
dimensions.
We first visualize the first 2
dimensions:
testdat <- lol.sims.cigar(n, d)
X <- testdat$X
Y <- testdat$Y
data <- data.frame(x1=X[,1], x2=X[,2], y=Y)
data$y <- factor(data$y)
ggplot(data, aes(x=x1, y=x2, color=y)) +
geom_point() +
xlab("x1") +
ylab("x2") +
ggtitle("Simulated Data")
Projecting with MDP to K-1=1
dimension and visualizing:
result <- lol.project.dp(X, Y)
data <- data.frame(x1=result$Xr[,1], y=Y)
data$y <- factor(data$y)
ggplot(data, aes(x=x1, y=y, color=y)) +
geom_point() +
xlab("x1") +
ylab("Class") +
ggtitle("Projected Data using MDP")
We visualize the first 2
dimensions:
testdat <- lol.sims.rtrunk(n, d)
X <- testdat$X
Y <- testdat$Y
data <- data.frame(x1=X[,1], x2=X[,2], y=Y)
data$y <- factor(data$y)
ggplot(data, aes(x=x1, y=x2, color=y)) +
geom_point() +
xlab("x1") +
ylab("x2") +
ggtitle("Simulated Data")
Projecting with MDP to K-1=1
dimensions and visualizing:
result <- lol.project.dp(X, Y)
data <- data.frame(x1=result$Xr[,1], y=Y)
data$y <- factor(data$y)
ggplot(data, aes(x=x1, y=y, color=y)) +
geom_point() +
xlab("x1") +
ylab("Class") +
ggtitle("Projected Data using MDP")
We visualize the first 2
dimensions:
testdat <- lol.sims.rtrunk(n, d, rotate=TRUE)
X <- testdat$X
Y <- testdat$Y
data <- data.frame(x1=X[,1], x2=X[,2], y=Y)
data$y <- factor(data$y)
ggplot(data, aes(x=x1, y=x2, color=y)) +
geom_point() +
xlab("x1") +
ylab("x2") +
ggtitle("Simulated Data")
Projecting with MDP to K-1=1
dimensions and visualizing:
result <- lol.project.dp(X, Y)
data <- data.frame(x1=result$Xr[,1], y=Y)
data$y <- factor(data$y)
ggplot(data, aes(x=x1, y=y, color=y)) +
geom_point() +
xlab("x1") +
ylab("Class") +
ggtitle("Projected Data using MDP")